MODELING OF THE HYDROMECHANICS OF DEFORMABLE FRACTURES

Carlo Vinci1, Jörg Renner2, Holger Steeb1

1 Institute of Mechanics, Ruhr-University Bochum, Germany 2 Institute of Geology, Mineralogy and Geophysics, Ruhr-University Bochum, Germany

www.lkm.rub.de vinci@lkm.rub.de

• Similarities of cloud and aerosol characteristics can indicate aerosol-cloud interactions (aci) in the vicinity of clouds

• Hydrated aerosols, activated cloud droplets and evaporating wispy clouds at the edge of clouds build up twilight zone where clouds and aerosols interact (Koren et al. 2007; Yang et al. 2012)

• Knowledge of their vertical and horizontal distribution over the globe and seasons will: • Contribute to the understanding of aerosol-cloud-meteorology

interactions • Reduce the uncertainty range of aci radiative forcing in climate

modelling

Spatial and Temporal Patterns of Aerosol-Cloud Interactions

Julia Fuchs, Jan Cermak Ruhr-Universität Bochum, Department of Geography/Climatology, Email: julia.fuchs@rub.de

Goal

I. Determine the spatial and temporal occurrence of regions with frequent hydrated aerosols

II. Identify scattering characteristics of hydrated aerosols

• Magnitude and altitude of hydrated aerosols follow seasonal and regional patterns

• Hydrated aerosols more frequent over continents and the northern hemisphere

• More frequent at altitudes of 8 km in July between 30° - 60°N compared to January, where hydrated aerosols occur at lower altitudes and are less frequent (I)

• Extraction of low CAD scores might present a method to analyze the seasonal and global occurrence of hydrated aerosols as scattering properties of the imaged feature show a valid range for hydrated aerosols (II)

• Enables global view on hydration of aerosols as part of current aci • Magnitude of hydrated aerosols gives implications for meteorological

regime in which aci take place

Rel. Frequencies of Hydrated Aerosols in August Aerosols Clouds Hydrated Aerosols

Koren, I., Remer, L. A., Kaufman, Y. J., Rudich, Y., & Martins, J. V. (2007). On the twilight zone between clouds and aerosols. Geophysical Research Letters, 34(8), 1–5. doi:10.1029/2007GL029253 Liu, Z., Kuehn, R., Vaughan, M., & Winker, D. (2010). The CALIPSO cloud and aerosol discrimination: Version 3 algorithm and test results. Yang, W., Marshak, A., Várnai, T., & Liu, Z. (2012). Effect of CALIPSO cloud–aerosol discrimination (CAD) confidence levels on observations of aerosol properties near clouds. Atmospheric Research, 116, 134–141. doi:10.1016/j.atmosres.2012.03.013

Fig.1: A cloud and the ‘‘twilight zone’’ taken by a digital camera (Koren et al. 2007)

• Cloud-Aerosol Discrimination (CAD) score from CALIPSO’s (Cloud-

Aerosol Lidar and Infrared Pathfinder Satellite Observations) L2 5km Layer Products separates aerosols and clouds according to multidimensional probability density functions (PDF) of 5 characteristics (5D):

attenuated backscatter, total color ratio, volume depolarization ratio, altitude and latitude

• CAD score ranges between -100 ( = aerosol), 0 ( = aerosol or cloud) and 100 ( = cloud) (Liu et al. 2010)

• Low CAD scores (-20 to 20) can indicate large hydrated aerosols and are extracted

• 10° boxes show relative frequency, altitude, seasonal difference and averaged scattering properties of low CAD values

• CAD values equal to zero and features below optically thick layers are excluded from the analysis

Fig. 3 : Mean altitudes of CAD values (-20 and 20) in August and during the cours of the years 2008/2009

Fig. 4: January – July difference of relative frequencies [%] of CAD values (-20 and 20) in August 2008/2009

Fig. 5: January – July difference of mean altitudes [km] of CAD values (-20 and 20) in August 2008/2009

Fig. 6: Mean attenuated back-scatter (CAD -20 and 20) in August 2008/2009

Fig. 7: Mean color ratio (CAD -20 and 20) in August 2008/2009

Fig. 8: Mean volume depolari-zation ratio (CAD -20 and 20) in August 2008/2009

Fig. 9: 2D distribution of feature occurrence numbers as a function of total color ratio and mean attenuated backscatter in August 2008/2009

Fig. 10: 2D distribution of feature occurrence numbers as a function of volume depolarization ratio and mean attenuated backscatter in August 2008/2009

Mean Altitudes of Hydrated Aerosols in August

Seasonal Pattern of Hydrated Aerosol Distribution

METHOD

RESULTS II: Scattering Characteristics

REFERENCES

CONCLUSIONS

RESULTS II: Scattering Characteristics RESULTS I: Frequencies and Altitudes MOTIVATION

Fig. 2: Relative frequencies of CAD values (-20 and 20) in August 2008/2009